Overview

Dataset statistics

Number of variables29
Number of observations47
Missing cells55
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory234.7 B

Variable types

Numeric9
Categorical20

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-19" Constant
_embedded_show_dvdCountry has constant value "nan" Constant
season is highly correlated with _embedded_show_updatedHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_updated is highly correlated with seasonHigh correlation
season is highly correlated with runtime and 2 other fieldsHigh correlation
number is highly correlated with _embedded_show_runtimeHigh correlation
runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_summary and 11 other fieldsHigh correlation
summary is highly correlated with url and 5 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_type is highly correlated with url and 5 other fieldsHigh correlation
_embedded_show_status is highly correlated with url and 7 other fieldsHigh correlation
url is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
image is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_status and 7 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
name is highly correlated with url and 6 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
airtime is highly correlated with url and 9 other fieldsHigh correlation
_links_self_href is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
_embedded_show_language is highly correlated with url and 7 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
id is highly correlated with url and 17 other fieldsHigh correlation
url is highly correlated with id and 24 other fieldsHigh correlation
name is highly correlated with id and 22 other fieldsHigh correlation
season is highly correlated with url and 13 other fieldsHigh correlation
number is highly correlated with url and 13 other fieldsHigh correlation
airtime is highly correlated with url and 14 other fieldsHigh correlation
airstamp is highly correlated with id and 18 other fieldsHigh correlation
runtime is highly correlated with id and 17 other fieldsHigh correlation
image is highly correlated with id and 24 other fieldsHigh correlation
summary is highly correlated with url and 11 other fieldsHigh correlation
_embedded_show_id is highly correlated with url and 13 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_type is highly correlated with url and 16 other fieldsHigh correlation
_embedded_show_language is highly correlated with url and 10 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_status is highly correlated with id and 11 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with id and 15 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 13 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 13 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 12 other fieldsHigh correlation
_links_self_href is highly correlated with id and 24 other fieldsHigh correlation
runtime has 5 (10.6%) missing values Missing
image has 32 (68.1%) missing values Missing
_embedded_show_runtime has 13 (27.7%) missing values Missing
_embedded_show_averageRuntime has 5 (10.6%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_embedded_show_url is uniformly distributed Uniform
_embedded_show_name is uniformly distributed Uniform
_embedded_show_premiered is uniformly distributed Uniform
_embedded_show_officialSite is uniformly distributed Uniform
_embedded_show_summary is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique
_embedded_show_weight has 1 (2.1%) zeros Zeros

Reproduction

Analysis started2022-05-10 02:17:01.599912
Analysis finished2022-05-10 02:17:21.023859
Duration19.42 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2051438.298
Minimum1943281
Maximum2318107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:21.095792image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1943281
5-th percentile1956038.7
Q11984912.5
median1997520
Q32112516.5
95-th percentile2289709
Maximum2318107
Range374826
Interquartile range (IQR)127604

Descriptive statistics

Standard deviation103634.4203
Coefficient of variation (CV)0.05051793196
Kurtosis0.7756323236
Mean2051438.298
Median Absolute Deviation (MAD)35462
Skewness1.337740001
Sum96417600
Variance1.074009308 × 1010
MonotonicityNot monotonic
2022-05-09T21:17:21.205180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
19888621
 
2.1%
22893241
 
2.1%
19975201
 
2.1%
19975211
 
2.1%
20000641
 
2.1%
20000651
 
2.1%
20311921
 
2.1%
20399371
 
2.1%
21183781
 
2.1%
21817971
 
2.1%
Other values (37)37
78.7%
ValueCountFrequency (%)
19432811
2.1%
19530701
2.1%
19537891
2.1%
19612881
2.1%
19620581
2.1%
19725711
2.1%
19725721
2.1%
19773271
2.1%
19832741
2.1%
19841811
2.1%
ValueCountFrequency (%)
23181071
2.1%
23112141
2.1%
22898741
2.1%
22893241
2.1%
22121671
2.1%
21821181
2.1%
21817971
2.1%
21761361
2.1%
21389261
2.1%
21376041
2.1%

url
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size504.0 B
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24
 
1
https://www.tvmaze.com/episodes/2289324/blippi-2020-12-19-blippi-visits-a-christmas-tree-farm-educational-videos-for-kids
 
1
https://www.tvmaze.com/episodes/1997520/the-penalty-zone-1x13-episode-13
 
1
https://www.tvmaze.com/episodes/1997521/the-penalty-zone-1x14-episode-14
 
1
https://www.tvmaze.com/episodes/2000064/ultimate-note-1x17-episode-17
 
1
Other values (42)
42 

Length

Max length122
Median length90
Mean length81.29787234
Min length53

Characters and Unicode

Total characters3821
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24
2nd rowhttps://www.tvmaze.com/episodes/1989501/troe-iz-prostokvasino-2x39-papa-ne-goruj
3rd rowhttps://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirint
4th rowhttps://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji
5th rowhttps://www.tvmaze.com/episodes/2138926/tokyo-joshi-pro-wrestling-2020-12-19-tjpw-seno-merry-christmas-2020

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-241
 
2.1%
https://www.tvmaze.com/episodes/2289324/blippi-2020-12-19-blippi-visits-a-christmas-tree-farm-educational-videos-for-kids1
 
2.1%
https://www.tvmaze.com/episodes/1997520/the-penalty-zone-1x13-episode-131
 
2.1%
https://www.tvmaze.com/episodes/1997521/the-penalty-zone-1x14-episode-141
 
2.1%
https://www.tvmaze.com/episodes/2000064/ultimate-note-1x17-episode-171
 
2.1%
https://www.tvmaze.com/episodes/2000065/ultimate-note-1x18-episode-181
 
2.1%
https://www.tvmaze.com/episodes/2031192/our-memory-1x03-episode-31
 
2.1%
https://www.tvmaze.com/episodes/2039937/tregayes-way-in-the-kitchen-1x06-soul-food-sunday1
 
2.1%
https://www.tvmaze.com/episodes/2118378/yaar-jigree-kasooti-degree-2x12-cracked1
 
2.1%
https://www.tvmaze.com/episodes/2181797/i-like-to-watch-3x09-dolly-partons-christmas-on-the-square1
 
2.1%
Other values (37)37
78.7%

Length

2022-05-09T21:17:21.330673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-241
 
2.1%
https://www.tvmaze.com/episodes/2212167/zombety-1x08-8-seria1
 
2.1%
https://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirint1
 
2.1%
https://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji1
 
2.1%
https://www.tvmaze.com/episodes/2138926/tokyo-joshi-pro-wrestling-2020-12-19-tjpw-seno-merry-christmas-20201
 
2.1%
https://www.tvmaze.com/episodes/1962058/heaven-officials-blessing-1x09-evil-taoist-scourge1
 
2.1%
https://www.tvmaze.com/episodes/1972571/the-wolf-1x29-episode-291
 
2.1%
https://www.tvmaze.com/episodes/1972572/the-wolf-1x30-episode-301
 
2.1%
https://www.tvmaze.com/episodes/2071487/youths-in-the-breeze-1x17-full-time-sworn-enemy-011
 
2.1%
https://www.tvmaze.com/episodes/2071488/youths-in-the-breeze-1x18-full-time-sworn-enemy-021
 
2.1%
Other values (37)37
78.7%

Most occurring characters

ValueCountFrequency (%)
e313
 
8.2%
-301
 
7.9%
t242
 
6.3%
s241
 
6.3%
/235
 
6.2%
o213
 
5.6%
w166
 
4.3%
i157
 
4.1%
1137
 
3.6%
p135
 
3.5%
Other values (30)1681
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2583
67.6%
Decimal Number561
 
14.7%
Other Punctuation376
 
9.8%
Dash Punctuation301
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e313
12.1%
t242
 
9.4%
s241
 
9.3%
o213
 
8.2%
w166
 
6.4%
i157
 
6.1%
p135
 
5.2%
a134
 
5.2%
m134
 
5.2%
d103
 
4.0%
Other values (16)745
28.8%
Decimal Number
ValueCountFrequency (%)
1137
24.4%
285
15.2%
071
12.7%
964
11.4%
855
9.8%
737
 
6.6%
335
 
6.2%
528
 
5.0%
427
 
4.8%
622
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/235
62.5%
.94
 
25.0%
:47
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2583
67.6%
Common1238
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e313
12.1%
t242
 
9.4%
s241
 
9.3%
o213
 
8.2%
w166
 
6.4%
i157
 
6.1%
p135
 
5.2%
a134
 
5.2%
m134
 
5.2%
d103
 
4.0%
Other values (16)745
28.8%
Common
ValueCountFrequency (%)
-301
24.3%
/235
19.0%
1137
11.1%
.94
 
7.6%
285
 
6.9%
071
 
5.7%
964
 
5.2%
855
 
4.4%
:47
 
3.8%
737
 
3.0%
Other values (4)112
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e313
 
8.2%
-301
 
7.9%
t242
 
6.3%
s241
 
6.3%
/235
 
6.2%
o213
 
5.6%
w166
 
4.3%
i157
 
4.1%
1137
 
3.6%
p135
 
3.5%
Other values (30)1681
44.0%

name
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size504.0 B
Episode 3
 
2
Chanyeol's Episode 24
 
1
Blippi Visits A Christmas Tree Farm | Educational Videos For Kids
 
1
Episode 13
 
1
Episode 14
 
1
Other values (41)
41 

Length

Max length70
Median length30
Mean length19.04255319
Min length3

Characters and Unicode

Total characters895
Distinct characters114
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st rowChanyeol's Episode 24
2nd rowПапа, не горюй
3rd rowСнежный лабиринт
4th row第135集
5th rowTJPW Se~No Merry Christmas! 2020

Common Values

ValueCountFrequency (%)
Episode 32
 
4.3%
Chanyeol's Episode 241
 
2.1%
Blippi Visits A Christmas Tree Farm | Educational Videos For Kids1
 
2.1%
Episode 131
 
2.1%
Episode 141
 
2.1%
Episode 171
 
2.1%
Episode 181
 
2.1%
Soul Food Sunday1
 
2.1%
CRACKED1
 
2.1%
Dolly Parton's Christmas on the Square1
 
2.1%
Other values (36)36
76.6%

Length

2022-05-09T21:17:21.456083image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode12
 
7.7%
the4
 
2.6%
christmas3
 
1.9%
193
 
1.9%
enemy2
 
1.3%
vs2
 
1.3%
не2
 
1.3%
20202
 
1.3%
sworn2
 
1.3%
full-time2
 
1.3%
Other values (114)122
78.2%

Most occurring characters

ValueCountFrequency (%)
109
 
12.2%
e61
 
6.8%
i46
 
5.1%
o45
 
5.0%
s42
 
4.7%
a33
 
3.7%
r32
 
3.6%
t32
 
3.6%
n27
 
3.0%
d26
 
2.9%
Other values (104)442
49.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter546
61.0%
Uppercase Letter146
 
16.3%
Space Separator109
 
12.2%
Decimal Number52
 
5.8%
Other Punctuation23
 
2.6%
Other Letter14
 
1.6%
Dash Punctuation3
 
0.3%
Math Symbol2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e61
 
11.2%
i46
 
8.4%
o45
 
8.2%
s42
 
7.7%
a33
 
6.0%
r32
 
5.9%
t32
 
5.9%
n27
 
4.9%
d26
 
4.8%
h20
 
3.7%
Other values (39)182
33.3%
Uppercase Letter
ValueCountFrequency (%)
E21
14.4%
F12
 
8.2%
S11
 
7.5%
T9
 
6.2%
N9
 
6.2%
C9
 
6.2%
D8
 
5.5%
M7
 
4.8%
P7
 
4.8%
R7
 
4.8%
Other values (19)46
31.5%
Other Letter
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4)4
28.6%
Decimal Number
ValueCountFrequency (%)
115
28.8%
07
13.5%
27
13.5%
96
 
11.5%
36
 
11.5%
84
 
7.7%
43
 
5.8%
52
 
3.8%
61
 
1.9%
71
 
1.9%
Other Punctuation
ValueCountFrequency (%)
,5
21.7%
:4
17.4%
!3
13.0%
.3
13.0%
#2
 
8.7%
'2
 
8.7%
?2
 
8.7%
"2
 
8.7%
Math Symbol
ValueCountFrequency (%)
|1
50.0%
~1
50.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin606
67.7%
Common189
 
21.1%
Cyrillic86
 
9.6%
Hangul12
 
1.3%
Han2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e61
 
10.1%
i46
 
7.6%
o45
 
7.4%
s42
 
6.9%
a33
 
5.4%
r32
 
5.3%
t32
 
5.3%
n27
 
4.5%
d26
 
4.3%
E21
 
3.5%
Other values (38)241
39.8%
Cyrillic
ValueCountFrequency (%)
и9
 
10.5%
н7
 
8.1%
о6
 
7.0%
а6
 
7.0%
р5
 
5.8%
е5
 
5.8%
к4
 
4.7%
т3
 
3.5%
й3
 
3.5%
я3
 
3.5%
Other values (20)35
40.7%
Common
ValueCountFrequency (%)
109
57.7%
115
 
7.9%
07
 
3.7%
27
 
3.7%
96
 
3.2%
36
 
3.2%
,5
 
2.6%
84
 
2.1%
:4
 
2.1%
43
 
1.6%
Other values (12)23
 
12.2%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII794
88.7%
Cyrillic86
 
9.6%
Hangul12
 
1.3%
CJK2
 
0.2%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
 
13.7%
e61
 
7.7%
i46
 
5.8%
o45
 
5.7%
s42
 
5.3%
a33
 
4.2%
r32
 
4.0%
t32
 
4.0%
n27
 
3.4%
d26
 
3.3%
Other values (59)341
42.9%
Cyrillic
ValueCountFrequency (%)
и9
 
10.5%
н7
 
8.1%
о6
 
7.0%
а6
 
7.0%
р5
 
5.8%
е5
 
5.8%
к4
 
4.7%
т3
 
3.5%
й3
 
3.5%
я3
 
3.5%
Other values (20)35
40.7%
None
ValueCountFrequency (%)
å1
100.0%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.6595745
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:21.567260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34.5
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation726.1838693
Coefficient of variation (CV)2.399342134
Kurtosis2.246181409
Mean302.6595745
Median Absolute Deviation (MAD)0
Skewness2.037723593
Sum14225
Variance527343.012
MonotonicityNot monotonic
2022-05-09T21:17:21.659431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
124
51.1%
20207
 
14.9%
25
 
10.6%
34
 
8.5%
42
 
4.3%
52
 
4.3%
71
 
2.1%
81
 
2.1%
61
 
2.1%
ValueCountFrequency (%)
124
51.1%
25
 
10.6%
34
 
8.5%
42
 
4.3%
52
 
4.3%
61
 
2.1%
71
 
2.1%
81
 
2.1%
20207
 
14.9%
ValueCountFrequency (%)
20207
 
14.9%
81
 
2.1%
71
 
2.1%
61
 
2.1%
52
 
4.3%
42
 
4.3%
34
 
8.5%
25
 
10.6%
124
51.1%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct25
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.91489362
Minimum3
Maximum346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:21.753727image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.3
Q16.5
median13
Q319
95-th percentile52.4
Maximum346
Range343
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation49.89764732
Coefficient of variation (CV)2.086467459
Kurtosis39.81287658
Mean23.91489362
Median Absolute Deviation (MAD)6
Skewness6.100368112
Sum1124
Variance2489.775208
MonotonicityNot monotonic
2022-05-09T21:17:21.848025image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
55
 
10.6%
64
 
8.5%
173
 
6.4%
183
 
6.4%
93
 
6.4%
123
 
6.4%
193
 
6.4%
32
 
4.3%
82
 
4.3%
142
 
4.3%
Other values (15)17
36.2%
ValueCountFrequency (%)
32
 
4.3%
41
 
2.1%
55
10.6%
64
8.5%
71
 
2.1%
82
 
4.3%
93
6.4%
102
 
4.3%
123
6.4%
131
 
2.1%
ValueCountFrequency (%)
3461
2.1%
541
2.1%
531
2.1%
511
2.1%
441
2.1%
401
2.1%
391
2.1%
302
4.3%
291
2.1%
241
2.1%

type
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size504.0 B
regular
47 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters329
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular47
100.0%

Length

2022-05-09T21:17:21.942254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:22.143833image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular47
100.0%

Most occurring characters

ValueCountFrequency (%)
r94
28.6%
e47
14.3%
g47
14.3%
u47
14.3%
l47
14.3%
a47
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter329
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r94
28.6%
e47
14.3%
g47
14.3%
u47
14.3%
l47
14.3%
a47
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin329
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r94
28.6%
e47
14.3%
g47
14.3%
u47
14.3%
l47
14.3%
a47
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r94
28.6%
e47
14.3%
g47
14.3%
u47
14.3%
l47
14.3%
a47
14.3%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size504.0 B
2020-12-19
47 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters470
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-19
2nd row2020-12-19
3rd row2020-12-19
4th row2020-12-19
5th row2020-12-19

Common Values

ValueCountFrequency (%)
2020-12-1947
100.0%

Length

2022-05-09T21:17:22.209368image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:22.288033image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1947
100.0%

Most occurring characters

ValueCountFrequency (%)
2141
30.0%
094
20.0%
-94
20.0%
194
20.0%
947
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number376
80.0%
Dash Punctuation94
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2141
37.5%
094
25.0%
194
25.0%
947
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2141
30.0%
094
20.0%
-94
20.0%
194
20.0%
947
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2141
30.0%
094
20.0%
-94
20.0%
194
20.0%
947
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
34 
06:00
 
2
11:00
 
2
10:00
 
1
12:00
 
1
Other values (7)

Length

Max length5
Median length3
Mean length3.553191489
Min length3

Characters and Unicode

Total characters167
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)19.1%

Sample

1st row06:00
2nd rownan
3rd rownan
4th row10:00
5th row12:00

Common Values

ValueCountFrequency (%)
nan34
72.3%
06:002
 
4.3%
11:002
 
4.3%
10:001
 
2.1%
12:001
 
2.1%
05:001
 
2.1%
17:001
 
2.1%
18:001
 
2.1%
00:151
 
2.1%
21:501
 
2.1%
Other values (2)2
 
4.3%

Length

2022-05-09T21:17:22.367071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan34
72.3%
06:002
 
4.3%
11:002
 
4.3%
10:001
 
2.1%
12:001
 
2.1%
05:001
 
2.1%
17:001
 
2.1%
18:001
 
2.1%
00:151
 
2.1%
21:501
 
2.1%
Other values (2)2
 
4.3%

Most occurring characters

ValueCountFrequency (%)
n68
40.7%
a34
20.4%
029
17.4%
:13
 
7.8%
111
 
6.6%
24
 
2.4%
63
 
1.8%
53
 
1.8%
71
 
0.6%
81
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter102
61.1%
Decimal Number52
31.1%
Other Punctuation13
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029
55.8%
111
 
21.2%
24
 
7.7%
63
 
5.8%
53
 
5.8%
71
 
1.9%
81
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
n68
66.7%
a34
33.3%
Other Punctuation
ValueCountFrequency (%)
:13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin102
61.1%
Common65
38.9%

Most frequent character per script

Common
ValueCountFrequency (%)
029
44.6%
:13
20.0%
111
 
16.9%
24
 
6.2%
63
 
4.6%
53
 
4.6%
71
 
1.5%
81
 
1.5%
Latin
ValueCountFrequency (%)
n68
66.7%
a34
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n68
40.7%
a34
20.4%
029
17.4%
:13
 
7.8%
111
 
6.6%
24
 
2.4%
63
 
1.8%
53
 
1.8%
71
 
0.6%
81
 
0.6%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct17
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size504.0 B
2020-12-19T12:00:00+00:00
20 
2020-12-19T04:00:00+00:00
2020-12-19T17:00:00+00:00
2020-12-19T03:00:00+00:00
 
2
2020-12-19T00:00:00+00:00
 
2
Other values (12)
13 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1175
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)23.4%

Sample

1st row2020-12-18T21:00:00+00:00
2nd row2020-12-19T00:00:00+00:00
3rd row2020-12-19T00:00:00+00:00
4th row2020-12-19T02:00:00+00:00
5th row2020-12-19T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-19T12:00:00+00:0020
42.6%
2020-12-19T04:00:00+00:005
 
10.6%
2020-12-19T17:00:00+00:005
 
10.6%
2020-12-19T03:00:00+00:002
 
4.3%
2020-12-19T00:00:00+00:002
 
4.3%
2020-12-19T11:00:00+00:002
 
4.3%
2020-12-18T21:00:00+00:001
 
2.1%
2020-12-19T15:15:00+00:001
 
2.1%
2020-12-19T21:00:00+00:001
 
2.1%
2020-12-19T20:50:00+00:001
 
2.1%
Other values (7)7
 
14.9%

Length

2022-05-09T21:17:22.477432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-19t12:00:00+00:0020
42.6%
2020-12-19t17:00:00+00:005
 
10.6%
2020-12-19t04:00:00+00:005
 
10.6%
2020-12-19t03:00:00+00:002
 
4.3%
2020-12-19t00:00:00+00:002
 
4.3%
2020-12-19t11:00:00+00:002
 
4.3%
2020-12-19t09:00:00+00:001
 
2.1%
2020-12-19t02:00:00+00:001
 
2.1%
2020-12-19t05:00:00+00:001
 
2.1%
2020-12-19t07:00:00+00:001
 
2.1%
Other values (7)7
 
14.9%

Most occurring characters

ValueCountFrequency (%)
0486
41.4%
2166
 
14.1%
:141
 
12.0%
1127
 
10.8%
-94
 
8.0%
T47
 
4.0%
+47
 
4.0%
946
 
3.9%
76
 
0.5%
45
 
0.4%
Other values (4)10
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number846
72.0%
Other Punctuation141
 
12.0%
Dash Punctuation94
 
8.0%
Uppercase Letter47
 
4.0%
Math Symbol47
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0486
57.4%
2166
 
19.6%
1127
 
15.0%
946
 
5.4%
76
 
0.7%
45
 
0.6%
54
 
0.5%
33
 
0.4%
82
 
0.2%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:141
100.0%
Dash Punctuation
ValueCountFrequency (%)
-94
100.0%
Uppercase Letter
ValueCountFrequency (%)
T47
100.0%
Math Symbol
ValueCountFrequency (%)
+47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1128
96.0%
Latin47
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0486
43.1%
2166
 
14.7%
:141
 
12.5%
1127
 
11.3%
-94
 
8.3%
+47
 
4.2%
946
 
4.1%
76
 
0.5%
45
 
0.4%
54
 
0.4%
Other values (3)6
 
0.5%
Latin
ValueCountFrequency (%)
T47
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0486
41.4%
2166
 
14.1%
:141
 
12.0%
1127
 
10.8%
-94
 
8.0%
T47
 
4.0%
+47
 
4.0%
946
 
3.9%
76
 
0.5%
45
 
0.4%
Other values (4)10
 
0.9%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct23
Distinct (%)54.8%
Missing5
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean41.80952381
Minimum5
Maximum335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:22.556070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.2
Q118.25
median27.5
Q345
95-th percentile117
Maximum335
Range330
Interquartile range (IQR)26.75

Descriptive statistics

Standard deviation52.69712729
Coefficient of variation (CV)1.26040965
Kurtosis24.13819481
Mean41.80952381
Median Absolute Deviation (MAD)16
Skewness4.515997777
Sum1756
Variance2776.987224
MonotonicityNot monotonic
2022-05-09T21:17:22.668629image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
457
14.9%
604
 
8.5%
303
 
6.4%
203
 
6.4%
152
 
4.3%
192
 
4.3%
162
 
4.3%
72
 
4.3%
252
 
4.3%
1202
 
4.3%
Other values (13)13
27.7%
(Missing)5
 
10.6%
ValueCountFrequency (%)
51
 
2.1%
72
4.3%
111
 
2.1%
121
 
2.1%
152
4.3%
162
4.3%
171
 
2.1%
181
 
2.1%
192
4.3%
203
6.4%
ValueCountFrequency (%)
3351
 
2.1%
1202
 
4.3%
604
8.5%
511
 
2.1%
501
 
2.1%
461
 
2.1%
457
14.9%
303
6.4%
291
 
2.1%
261
 
2.1%

image
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct15
Distinct (%)100.0%
Missing32
Missing (%)68.1%
Memory size504.0 B
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg'}
 
1
Other values (10)
10 

Length

Max length178
Median length176
Mean length176.1333333
Min length176

Characters and Unicode

Total characters2642
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/731119.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/731119.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721376.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721376.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/724599.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/724599.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/724600.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/724600.jpg'}1
 
2.1%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/724853.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/724853.jpg'}1
 
2.1%
Other values (5)5
 
10.6%
(Missing)32
68.1%

Length

2022-05-09T21:17:22.787519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium15
25.0%
original15
25.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724599.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721046.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/329/823876.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/329/823876.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/727216.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727216.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/404/1010042.jpg1
 
1.7%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1010042.jpg1
 
1.7%
Other values (22)22
36.7%

Most occurring characters

ValueCountFrequency (%)
/210
 
7.9%
a180
 
6.8%
t165
 
6.2%
m150
 
5.7%
i150
 
5.7%
s135
 
5.1%
e120
 
4.5%
'120
 
4.5%
o105
 
4.0%
p105
 
4.0%
Other values (28)1202
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1770
67.0%
Other Punctuation495
 
18.7%
Decimal Number272
 
10.3%
Space Separator45
 
1.7%
Connector Punctuation30
 
1.1%
Close Punctuation15
 
0.6%
Open Punctuation15
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a180
 
10.2%
t165
 
9.3%
m150
 
8.5%
i150
 
8.5%
s135
 
7.6%
e120
 
6.8%
o105
 
5.9%
p105
 
5.9%
u90
 
5.1%
c90
 
5.1%
Other values (9)480
27.1%
Decimal Number
ValueCountFrequency (%)
258
21.3%
932
11.8%
832
11.8%
730
11.0%
026
9.6%
122
 
8.1%
322
 
8.1%
620
 
7.4%
420
 
7.4%
510
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/210
42.4%
'120
24.2%
.90
18.2%
:60
 
12.1%
,15
 
3.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Connector Punctuation
ValueCountFrequency (%)
_30
100.0%
Close Punctuation
ValueCountFrequency (%)
}15
100.0%
Open Punctuation
ValueCountFrequency (%)
{15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1770
67.0%
Common872
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/210
24.1%
'120
13.8%
.90
10.3%
:60
 
6.9%
258
 
6.7%
45
 
5.2%
932
 
3.7%
832
 
3.7%
_30
 
3.4%
730
 
3.4%
Other values (9)165
18.9%
Latin
ValueCountFrequency (%)
a180
 
10.2%
t165
 
9.3%
m150
 
8.5%
i150
 
8.5%
s135
 
7.6%
e120
 
6.8%
o105
 
5.9%
p105
 
5.9%
u90
 
5.1%
c90
 
5.1%
Other values (9)480
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/210
 
7.9%
a180
 
6.8%
t165
 
6.2%
m150
 
5.7%
i150
 
5.7%
s135
 
5.1%
e120
 
4.5%
'120
 
4.5%
o105
 
4.0%
p105
 
4.0%
Other values (28)1202
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
37 
<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>
 
1
<p>The Japanese make gains in Malaya, Burma, Hong Kong, Borneo, and the Philippines. The Allies also have trouble in the Atlantic and the Mediterranean, where they are beginning to seriously suffer from a lack of capital ships. The Soviet Red Army is advancing, though, and Stalin takes personal control of planning for the upcoming counteroffensive, while Adolf Hitler takes personal control of the German Army.</p>
 
1
<p>Chai, a handsome man, and his friend Om were taking videos secretly and sell the video clips via an "Open Chat" software called "XTH Room". As both encounter a new victim, nothing will be the same.</p>
 
1
<p>Yun-hsiang becomes a target of slander, Shen Hua caves under pressure from his father, and Jui-hsin watches Yun-hsiang carry out an act of desperation.</p><p><br /> </p>
 
1
Other values (6)

Length

Max length416
Median length3
Mean length46.5106383
Min length3

Characters and Unicode

Total characters2186
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)21.3%

Sample

1st row<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan37
78.7%
<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>1
 
2.1%
<p>The Japanese make gains in Malaya, Burma, Hong Kong, Borneo, and the Philippines. The Allies also have trouble in the Atlantic and the Mediterranean, where they are beginning to seriously suffer from a lack of capital ships. The Soviet Red Army is advancing, though, and Stalin takes personal control of planning for the upcoming counteroffensive, while Adolf Hitler takes personal control of the German Army.</p>1
 
2.1%
<p>Chai, a handsome man, and his friend Om were taking videos secretly and sell the video clips via an "Open Chat" software called "XTH Room". As both encounter a new victim, nothing will be the same.</p>1
 
2.1%
<p>Yun-hsiang becomes a target of slander, Shen Hua caves under pressure from his father, and Jui-hsin watches Yun-hsiang carry out an act of desperation.</p><p><br /> </p>1
 
2.1%
<p>Yun-hsiang becomes trapped in a parallel consciousness. Cheng Wen-liang seeks his uncle's aid in preventing Jui-hsin's vengeful plan.</p><p><br /> </p>1
 
2.1%
<p>Tregaye Fraser prepares a Sunday feast for her family with love, laughs, stories and great food! She makes her Grandma's Mac and Cheese, Smothered Pork Chops and Collard Greens.</p>1
 
2.1%
<p>Always alone at school, Yamasato was able to live away from reality by writing his fantasy stories in his notebook. In the story, he is the center of the world, and the heroine, by default, is Ai (Hashimoto Ai), the popular girl at the school. But one day when he opened his notebook, he found the rest of the story he had never written... </p>1
 
2.1%
<p><b>"</b><i>It's all out war in Atlas. Our heroes face an impossible problem. Where do they go from here?</i><b>"</b></p>1
 
2.1%
<p>Chef Lovely creates an elegant dinner for close friends. She makes her Roasted Chicken with Pomegranate Glaze, Green Beans Over Lemon Ricotta and Sweet Potato and Gruyere Gratin. Plus, there's an Upside-Down Pear Tart for dessert. You can taste the love!</p>1
 
2.1%

Length

2022-05-09T21:17:22.930080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan37
 
10.1%
the19
 
5.2%
and12
 
3.3%
a8
 
2.2%
of8
 
2.2%
in7
 
1.9%
his6
 
1.6%
from5
 
1.4%
for5
 
1.4%
an5
 
1.4%
Other values (220)253
69.3%

Most occurring characters

ValueCountFrequency (%)
315
14.4%
e205
 
9.4%
n193
 
8.8%
a175
 
8.0%
o110
 
5.0%
r104
 
4.8%
s104
 
4.8%
t102
 
4.7%
i92
 
4.2%
h87
 
4.0%
Other values (51)699
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1613
73.8%
Space Separator318
 
14.5%
Uppercase Letter92
 
4.2%
Other Punctuation84
 
3.8%
Math Symbol68
 
3.1%
Dash Punctuation7
 
0.3%
Open Punctuation2
 
0.1%
Close Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e205
12.7%
n193
12.0%
a175
10.8%
o110
 
6.8%
r104
 
6.4%
s104
 
6.4%
t102
 
6.3%
i92
 
5.7%
h87
 
5.4%
l67
 
4.2%
Other values (14)374
23.2%
Uppercase Letter
ValueCountFrequency (%)
A12
13.0%
C8
 
8.7%
S8
 
8.7%
T8
 
8.7%
G7
 
7.6%
P6
 
6.5%
H5
 
5.4%
R5
 
5.4%
Y5
 
5.4%
O4
 
4.3%
Other values (12)24
26.1%
Other Punctuation
ValueCountFrequency (%)
,27
32.1%
.21
25.0%
/18
21.4%
"6
 
7.1%
'6
 
7.1%
#3
 
3.6%
!2
 
2.4%
?1
 
1.2%
Space Separator
ValueCountFrequency (%)
315
99.1%
 3
 
0.9%
Math Symbol
ValueCountFrequency (%)
>34
50.0%
<34
50.0%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1705
78.0%
Common481
 
22.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e205
12.0%
n193
11.3%
a175
 
10.3%
o110
 
6.5%
r104
 
6.1%
s104
 
6.1%
t102
 
6.0%
i92
 
5.4%
h87
 
5.1%
l67
 
3.9%
Other values (36)466
27.3%
Common
ValueCountFrequency (%)
315
65.5%
>34
 
7.1%
<34
 
7.1%
,27
 
5.6%
.21
 
4.4%
/18
 
3.7%
-7
 
1.5%
"6
 
1.2%
'6
 
1.2%
 3
 
0.6%
Other values (5)10
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2183
99.9%
None3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315
14.4%
e205
 
9.4%
n193
 
8.8%
a175
 
8.0%
o110
 
5.0%
r104
 
4.8%
s104
 
4.8%
t102
 
4.7%
i92
 
4.2%
h87
 
4.0%
Other values (50)696
31.9%
None
ValueCountFrequency (%)
 3
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46208.65957
Minimum1596
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:23.049228image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1596
5-th percentile10892
Q143220
median51125
Q354325
95-th percentile60836.3
Maximum61755
Range60159
Interquartile range (IQR)11105

Descriptive statistics

Standard deviation15009.73174
Coefficient of variation (CV)0.3248250842
Kurtosis2.320244183
Mean46208.65957
Median Absolute Deviation (MAD)3637
Skewness-1.735525116
Sum2171807
Variance225292046.8
MonotonicityNot monotonic
2022-05-09T21:17:23.178446image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
511252
 
4.3%
479122
 
4.3%
108922
 
4.3%
527432
 
4.3%
547622
 
4.3%
528062
 
4.3%
537541
 
2.1%
509391
 
2.1%
508391
 
2.1%
252941
 
2.1%
Other values (31)31
66.0%
ValueCountFrequency (%)
15961
2.1%
40911
2.1%
108922
4.3%
196671
2.1%
252941
2.1%
306061
2.1%
355511
2.1%
368401
2.1%
402321
2.1%
416481
2.1%
ValueCountFrequency (%)
617551
2.1%
615361
2.1%
608481
2.1%
608091
2.1%
588441
2.1%
579561
2.1%
579451
2.1%
566051
2.1%
560671
2.1%
559191
2.1%

_embedded_show_url
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size504.0 B
https://www.tvmaze.com/shows/51125/detention
 
2
https://www.tvmaze.com/shows/47912/the-wolf
 
2
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
 
2
https://www.tvmaze.com/shows/52743/the-penalty-zone
 
2
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
 
2
Other values (36)
37 

Length

Max length64
Median length56
Mean length50.38297872
Min length38

Characters and Unicode

Total characters2368
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)74.5%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
3rd rowhttps://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
4th rowhttps://www.tvmaze.com/shows/35551/soul-land
5th rowhttps://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/51125/detention2
 
4.3%
https://www.tvmaze.com/shows/47912/the-wolf2
 
4.3%
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino2
 
4.3%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
4.3%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
4.3%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
4.3%
https://www.tvmaze.com/shows/53754/lovely-bites-by-chef-lovely1
 
2.1%
https://www.tvmaze.com/shows/50939/rail-romanesque1
 
2.1%
https://www.tvmaze.com/shows/50839/um-actually1
 
2.1%
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims1
 
2.1%
Other values (31)31
66.0%

Length

2022-05-09T21:17:23.307350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/51125/detention2
 
4.3%
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino2
 
4.3%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
4.3%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
4.3%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
4.3%
https://www.tvmaze.com/shows/47912/the-wolf2
 
4.3%
https://www.tvmaze.com/shows/53888/fandom-tour1
 
2.1%
https://www.tvmaze.com/shows/35551/soul-land1
 
2.1%
https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling1
 
2.1%
https://www.tvmaze.com/shows/51670/heaven-officials-blessing1
 
2.1%
Other values (31)31
66.0%

Most occurring characters

ValueCountFrequency (%)
/235
 
9.9%
w205
 
8.7%
t197
 
8.3%
s182
 
7.7%
o154
 
6.5%
e126
 
5.3%
h117
 
4.9%
m110
 
4.6%
.94
 
4.0%
a85
 
3.6%
Other values (30)863
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1673
70.7%
Other Punctuation376
 
15.9%
Decimal Number237
 
10.0%
Dash Punctuation82
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w205
12.3%
t197
11.8%
s182
10.9%
o154
9.2%
e126
 
7.5%
h117
 
7.0%
m110
 
6.6%
a85
 
5.1%
c59
 
3.5%
p57
 
3.4%
Other values (16)381
22.8%
Decimal Number
ValueCountFrequency (%)
544
18.6%
426
11.0%
624
10.1%
023
9.7%
122
9.3%
222
9.3%
921
8.9%
820
8.4%
318
7.6%
717
 
7.2%
Other Punctuation
ValueCountFrequency (%)
/235
62.5%
.94
 
25.0%
:47
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1673
70.7%
Common695
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w205
12.3%
t197
11.8%
s182
10.9%
o154
9.2%
e126
 
7.5%
h117
 
7.0%
m110
 
6.6%
a85
 
5.1%
c59
 
3.5%
p57
 
3.4%
Other values (16)381
22.8%
Common
ValueCountFrequency (%)
/235
33.8%
.94
 
13.5%
-82
 
11.8%
:47
 
6.8%
544
 
6.3%
426
 
3.7%
624
 
3.5%
023
 
3.3%
122
 
3.2%
222
 
3.2%
Other values (4)76
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/235
 
9.9%
w205
 
8.7%
t197
 
8.3%
s182
 
7.7%
o154
 
6.5%
e126
 
5.3%
h117
 
4.9%
m110
 
4.6%
.94
 
4.0%
a85
 
3.6%
Other values (30)863
36.4%

_embedded_show_name
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size504.0 B
Detention
 
2
The Wolf
 
2
Трое из Простоквашино
 
2
The Penalty Zone
 
2
Youths in the Breeze
 
2
Other values (36)
37 

Length

Max length30
Median length22
Mean length15.61702128
Min length4

Characters and Unicode

Total characters734
Distinct characters81
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)74.5%

Sample

1st rowSim for You
2nd rowТрое из Простоквашино
3rd rowТрое из Простоквашино
4th rowSoul Land
5th rowTokyo Joshi Pro Wrestling

Common Values

ValueCountFrequency (%)
Detention2
 
4.3%
The Wolf2
 
4.3%
Трое из Простоквашино2
 
4.3%
The Penalty Zone2
 
4.3%
Youths in the Breeze2
 
4.3%
Ultimate Note2
 
4.3%
Lovely Bites by Chef Lovely1
 
2.1%
Rail Romanesque1
 
2.1%
Um, Actually...1
 
2.1%
UFC Fight Pass Prelims1
 
2.1%
Other values (31)31
66.0%

Length

2022-05-09T21:17:23.435217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the8
 
6.2%
in3
 
2.3%
detention2
 
1.6%
ultimate2
 
1.6%
to2
 
1.6%
world2
 
1.6%
fight2
 
1.6%
ufc2
 
1.6%
by2
 
1.6%
lovely2
 
1.6%
Other values (92)102
79.1%

Most occurring characters

ValueCountFrequency (%)
82
 
11.2%
e73
 
9.9%
o42
 
5.7%
i41
 
5.6%
t40
 
5.4%
n33
 
4.5%
a30
 
4.1%
s28
 
3.8%
r26
 
3.5%
l24
 
3.3%
Other values (71)315
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter515
70.2%
Uppercase Letter124
 
16.9%
Space Separator82
 
11.2%
Other Punctuation9
 
1.2%
Decimal Number4
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e73
14.2%
o42
 
8.2%
i41
 
8.0%
t40
 
7.8%
n33
 
6.4%
a30
 
5.8%
s28
 
5.4%
r26
 
5.0%
l24
 
4.7%
h19
 
3.7%
Other values (37)159
30.9%
Uppercase Letter
ValueCountFrequency (%)
W14
 
11.3%
T11
 
8.9%
B9
 
7.3%
S9
 
7.3%
D8
 
6.5%
U6
 
4.8%
Y6
 
4.8%
P5
 
4.0%
O5
 
4.0%
F5
 
4.0%
Other values (16)46
37.1%
Other Punctuation
ValueCountFrequency (%)
'3
33.3%
.3
33.3%
,1
 
11.1%
?1
 
11.1%
:1
 
11.1%
Decimal Number
ValueCountFrequency (%)
22
50.0%
02
50.0%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin585
79.7%
Common95
 
12.9%
Cyrillic54
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e73
 
12.5%
o42
 
7.2%
i41
 
7.0%
t40
 
6.8%
n33
 
5.6%
a30
 
5.1%
s28
 
4.8%
r26
 
4.4%
l24
 
4.1%
h19
 
3.2%
Other values (40)229
39.1%
Cyrillic
ValueCountFrequency (%)
о12
22.2%
и4
 
7.4%
р4
 
7.4%
е3
 
5.6%
т3
 
5.6%
м2
 
3.7%
ш2
 
3.7%
с2
 
3.7%
з2
 
3.7%
П2
 
3.7%
Other values (13)18
33.3%
Common
ValueCountFrequency (%)
82
86.3%
'3
 
3.2%
.3
 
3.2%
22
 
2.1%
02
 
2.1%
,1
 
1.1%
?1
 
1.1%
:1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII678
92.4%
Cyrillic54
 
7.4%
None2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
 
12.1%
e73
 
10.8%
o42
 
6.2%
i41
 
6.0%
t40
 
5.9%
n33
 
4.9%
a30
 
4.4%
s28
 
4.1%
r26
 
3.8%
l24
 
3.5%
Other values (46)259
38.2%
Cyrillic
ValueCountFrequency (%)
о12
22.2%
и4
 
7.4%
р4
 
7.4%
е3
 
5.6%
т3
 
5.6%
м2
 
3.7%
ш2
 
3.7%
с2
 
3.7%
з2
 
3.7%
П2
 
3.7%
Other values (13)18
33.3%
None
ValueCountFrequency (%)
å1
50.0%
ø1
50.0%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size504.0 B
Scripted
22 
Animation
Documentary
Sports
Reality
Other values (3)

Length

Max length11
Median length9
Mean length8.319148936
Min length6

Characters and Unicode

Total characters391
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st rowReality
2nd rowAnimation
3rd rowAnimation
4th rowAnimation
5th rowSports

Common Values

ValueCountFrequency (%)
Scripted22
46.8%
Animation7
 
14.9%
Documentary5
 
10.6%
Sports4
 
8.5%
Reality3
 
6.4%
Talk Show3
 
6.4%
Game Show2
 
4.3%
Variety1
 
2.1%

Length

2022-05-09T21:17:23.546517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:23.647050image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted22
42.3%
animation7
 
13.5%
documentary5
 
9.6%
show5
 
9.6%
sports4
 
7.7%
reality3
 
5.8%
talk3
 
5.8%
game2
 
3.8%
variety1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
t42
10.7%
i40
10.2%
e33
 
8.4%
r32
 
8.2%
S31
 
7.9%
c27
 
6.9%
p26
 
6.6%
d22
 
5.6%
a21
 
5.4%
o21
 
5.4%
Other values (16)96
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter334
85.4%
Uppercase Letter52
 
13.3%
Space Separator5
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t42
12.6%
i40
12.0%
e33
9.9%
r32
9.6%
c27
8.1%
p26
7.8%
d22
6.6%
a21
6.3%
o21
6.3%
n19
 
5.7%
Other values (8)51
15.3%
Uppercase Letter
ValueCountFrequency (%)
S31
59.6%
A7
 
13.5%
D5
 
9.6%
T3
 
5.8%
R3
 
5.8%
G2
 
3.8%
V1
 
1.9%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin386
98.7%
Common5
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t42
10.9%
i40
10.4%
e33
 
8.5%
r32
 
8.3%
S31
 
8.0%
c27
 
7.0%
p26
 
6.7%
d22
 
5.7%
a21
 
5.4%
o21
 
5.4%
Other values (15)91
23.6%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t42
10.7%
i40
10.2%
e33
 
8.4%
r32
 
8.2%
S31
 
7.9%
c27
 
6.9%
p26
 
6.6%
d22
 
5.6%
a21
 
5.4%
o21
 
5.4%
Other values (16)96
24.6%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size504.0 B
English
14 
Chinese
13 
Norwegian
Russian
Korean
Other values (6)

Length

Max length9
Median length7
Mean length7.085106383
Min length4

Characters and Unicode

Total characters333
Distinct characters27
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)10.6%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowJapanese

Common Values

ValueCountFrequency (%)
English14
29.8%
Chinese13
27.7%
Norwegian5
 
10.6%
Russian4
 
8.5%
Korean3
 
6.4%
Japanese3
 
6.4%
Dutch1
 
2.1%
Thai1
 
2.1%
Tagalog1
 
2.1%
Panjabi1
 
2.1%

Length

2022-05-09T21:17:23.760316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english14
29.8%
chinese13
27.7%
norwegian5
 
10.6%
russian4
 
8.5%
korean3
 
6.4%
japanese3
 
6.4%
dutch1
 
2.1%
thai1
 
2.1%
tagalog1
 
2.1%
panjabi1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
n43
12.9%
e40
12.0%
i39
11.7%
s38
11.4%
h29
8.7%
a24
7.2%
g21
 
6.3%
l15
 
4.5%
E14
 
4.2%
C13
 
3.9%
Other values (17)57
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter286
85.9%
Uppercase Letter47
 
14.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n43
15.0%
e40
14.0%
i39
13.6%
s38
13.3%
h29
10.1%
a24
8.4%
g21
7.3%
l15
 
5.2%
r9
 
3.1%
o9
 
3.1%
Other values (7)19
6.6%
Uppercase Letter
ValueCountFrequency (%)
E14
29.8%
C13
27.7%
N5
 
10.6%
R4
 
8.5%
J3
 
6.4%
K3
 
6.4%
T2
 
4.3%
D1
 
2.1%
P1
 
2.1%
A1
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin333
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n43
12.9%
e40
12.0%
i39
11.7%
s38
11.4%
h29
8.7%
a24
7.2%
g21
 
6.3%
l15
 
4.5%
E14
 
4.2%
C13
 
3.9%
Other values (17)57
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n43
12.9%
e40
12.0%
i39
11.7%
s38
11.4%
h29
8.7%
a24
7.2%
g21
 
6.3%
l15
 
4.5%
E14
 
4.2%
C13
 
3.9%
Other values (17)57
17.1%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct25
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size504.0 B
[]
13 
['Drama', 'Romance']
['Drama', 'Action', 'Crime']
 
2
['Drama', 'Romance', 'History']
 
2
['Drama', 'Fantasy']
 
2
Other values (20)
24 

Length

Max length51
Median length40
Mean length18.44680851
Min length2

Characters and Unicode

Total characters867
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)34.0%

Sample

1st row[]
2nd row['Children', 'Family']
3rd row['Children', 'Family']
4th row['Action', 'Adventure', 'Anime', 'Fantasy']
5th row[]

Common Values

ValueCountFrequency (%)
[]13
27.7%
['Drama', 'Romance']4
 
8.5%
['Drama', 'Action', 'Crime']2
 
4.3%
['Drama', 'Romance', 'History']2
 
4.3%
['Drama', 'Fantasy']2
 
4.3%
['Comedy']2
 
4.3%
['Children', 'Family']2
 
4.3%
['Drama', 'Comedy', 'Adventure']2
 
4.3%
['Drama', 'Horror', 'Thriller']2
 
4.3%
['Comedy', 'Anime', 'Science-Fiction']1
 
2.1%
Other values (15)15
31.9%

Length

2022-05-09T21:17:23.876635image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama19
20.2%
13
13.8%
romance8
8.5%
comedy8
8.5%
fantasy5
 
5.3%
adventure5
 
5.3%
action5
 
5.3%
children4
 
4.3%
horror4
 
4.3%
anime4
 
4.3%
Other values (11)19
20.2%

Most occurring characters

ValueCountFrequency (%)
'162
18.7%
a62
 
7.2%
r54
 
6.2%
[47
 
5.4%
]47
 
5.4%
,47
 
5.4%
47
 
5.4%
e45
 
5.2%
m44
 
5.1%
o37
 
4.3%
Other values (23)275
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter432
49.8%
Other Punctuation209
24.1%
Uppercase Letter83
 
9.6%
Open Punctuation47
 
5.4%
Close Punctuation47
 
5.4%
Space Separator47
 
5.4%
Dash Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a62
14.4%
r54
12.5%
e45
10.4%
m44
10.2%
o37
8.6%
n35
8.1%
i30
6.9%
t22
 
5.1%
y21
 
4.9%
c20
 
4.6%
Other values (7)62
14.4%
Uppercase Letter
ValueCountFrequency (%)
D19
22.9%
C14
16.9%
A14
16.9%
F11
13.3%
R8
9.6%
H7
 
8.4%
T4
 
4.8%
S3
 
3.6%
M2
 
2.4%
W1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
'162
77.5%
,47
 
22.5%
Open Punctuation
ValueCountFrequency (%)
[47
100.0%
Close Punctuation
ValueCountFrequency (%)
]47
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin515
59.4%
Common352
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a62
12.0%
r54
 
10.5%
e45
 
8.7%
m44
 
8.5%
o37
 
7.2%
n35
 
6.8%
i30
 
5.8%
t22
 
4.3%
y21
 
4.1%
c20
 
3.9%
Other values (17)145
28.2%
Common
ValueCountFrequency (%)
'162
46.0%
[47
 
13.4%
]47
 
13.4%
,47
 
13.4%
47
 
13.4%
-2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'162
18.7%
a62
 
7.2%
r54
 
6.2%
[47
 
5.4%
]47
 
5.4%
,47
 
5.4%
47
 
5.4%
e45
 
5.2%
m44
 
5.1%
o37
 
4.3%
Other values (23)275
31.7%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size504.0 B
Running
26 
Ended
16 
To Be Determined

Length

Max length16
Median length7
Mean length7.276595745
Min length5

Characters and Unicode

Total characters342
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running26
55.3%
Ended16
34.0%
To Be Determined5
 
10.6%

Length

2022-05-09T21:17:23.981223image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:24.061982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running26
45.6%
ended16
28.1%
to5
 
8.8%
be5
 
8.8%
determined5
 
8.8%

Most occurring characters

ValueCountFrequency (%)
n99
28.9%
d37
 
10.8%
e36
 
10.5%
i31
 
9.1%
R26
 
7.6%
u26
 
7.6%
g26
 
7.6%
E16
 
4.7%
10
 
2.9%
T5
 
1.5%
Other values (6)30
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter275
80.4%
Uppercase Letter57
 
16.7%
Space Separator10
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n99
36.0%
d37
 
13.5%
e36
 
13.1%
i31
 
11.3%
u26
 
9.5%
g26
 
9.5%
o5
 
1.8%
t5
 
1.8%
r5
 
1.8%
m5
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
R26
45.6%
E16
28.1%
T5
 
8.8%
B5
 
8.8%
D5
 
8.8%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin332
97.1%
Common10
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n99
29.8%
d37
 
11.1%
e36
 
10.8%
i31
 
9.3%
R26
 
7.8%
u26
 
7.8%
g26
 
7.8%
E16
 
4.8%
T5
 
1.5%
o5
 
1.5%
Other values (5)25
 
7.5%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n99
28.9%
d37
 
10.8%
e36
 
10.5%
i31
 
9.1%
R26
 
7.6%
u26
 
7.6%
g26
 
7.6%
E16
 
4.7%
10
 
2.9%
T5
 
1.5%
Other values (6)30
 
8.8%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct12
Distinct (%)35.3%
Missing13
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean35.70588235
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:24.143238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q117
median25
Q345
95-th percentile120
Maximum120
Range115
Interquartile range (IQR)28

Descriptive statistics

Standard deviation30.53912484
Coefficient of variation (CV)0.8552967419
Kurtosis3.267210736
Mean35.70588235
Median Absolute Deviation (MAD)16
Skewness1.861814839
Sum1214
Variance932.6381462
MonotonicityNot monotonic
2022-05-09T21:17:24.245831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
457
14.9%
255
 
10.6%
74
 
8.5%
304
 
8.5%
203
 
6.4%
1203
 
6.4%
152
 
4.3%
602
 
4.3%
161
 
2.1%
111
 
2.1%
Other values (2)2
 
4.3%
(Missing)13
27.7%
ValueCountFrequency (%)
51
 
2.1%
74
8.5%
111
 
2.1%
152
 
4.3%
161
 
2.1%
203
6.4%
241
 
2.1%
255
10.6%
304
8.5%
457
14.9%
ValueCountFrequency (%)
1203
6.4%
602
 
4.3%
457
14.9%
304
8.5%
255
10.6%
241
 
2.1%
203
6.4%
161
 
2.1%
152
 
4.3%
111
 
2.1%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)61.9%
Missing5
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean36.83333333
Minimum5
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:24.437407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.1
Q115.25
median26.5
Q345
95-th percentile117.7
Maximum190
Range185
Interquartile range (IQR)29.75

Descriptive statistics

Standard deviation35.26825192
Coefficient of variation (CV)0.9575091019
Kurtosis8.720615025
Mean36.83333333
Median Absolute Deviation (MAD)15.5
Skewness2.667866835
Sum1547
Variance1243.849593
MonotonicityNot monotonic
2022-05-09T21:17:24.534159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
456
 
12.8%
153
 
6.4%
303
 
6.4%
172
 
4.3%
202
 
4.3%
1202
 
4.3%
252
 
4.3%
72
 
4.3%
512
 
4.3%
112
 
4.3%
Other values (16)16
34.0%
(Missing)5
 
10.6%
ValueCountFrequency (%)
51
 
2.1%
72
4.3%
91
 
2.1%
101
 
2.1%
112
4.3%
131
 
2.1%
153
6.4%
161
 
2.1%
172
4.3%
202
4.3%
ValueCountFrequency (%)
1901
 
2.1%
1202
 
4.3%
741
 
2.1%
601
 
2.1%
561
 
2.1%
512
 
4.3%
456
12.8%
431
 
2.1%
391
 
2.1%
303
6.4%

_embedded_show_premiered
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct38
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Memory size504.0 B
2020-12-05
 
3
2020-10-03
 
2
2020-12-13
 
2
1978-06-10
 
2
2020-11-14
 
2
Other values (33)
36 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters470
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)63.8%

Sample

1st row2019-03-25
2nd row1978-06-10
3rd row1978-06-10
4th row2018-01-13
5th row2013-01-30

Common Values

ValueCountFrequency (%)
2020-12-053
 
6.4%
2020-10-032
 
4.3%
2020-12-132
 
4.3%
1978-06-102
 
4.3%
2020-11-142
 
4.3%
2020-12-162
 
4.3%
2020-12-102
 
4.3%
2020-11-192
 
4.3%
2017-01-151
 
2.1%
2016-08-021
 
2.1%
Other values (28)28
59.6%

Length

2022-05-09T21:17:24.642666image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-053
 
6.4%
2020-12-132
 
4.3%
1978-06-102
 
4.3%
2020-11-142
 
4.3%
2020-12-162
 
4.3%
2020-12-102
 
4.3%
2020-11-192
 
4.3%
2020-10-032
 
4.3%
2020-09-191
 
2.1%
2016-12-171
 
2.1%
Other values (28)28
59.6%

Most occurring characters

ValueCountFrequency (%)
0117
24.9%
297
20.6%
-94
20.0%
189
18.9%
919
 
4.0%
312
 
2.6%
811
 
2.3%
610
 
2.1%
79
 
1.9%
58
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number376
80.0%
Dash Punctuation94
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0117
31.1%
297
25.8%
189
23.7%
919
 
5.1%
312
 
3.2%
811
 
2.9%
610
 
2.7%
79
 
2.4%
58
 
2.1%
44
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
-94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0117
24.9%
297
20.6%
-94
20.0%
189
18.9%
919
 
4.0%
312
 
2.6%
811
 
2.3%
610
 
2.1%
79
 
1.9%
58
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0117
24.9%
297
20.6%
-94
20.0%
189
18.9%
919
 
4.0%
312
 
2.6%
811
 
2.3%
610
 
2.1%
79
 
1.9%
58
 
1.7%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
31 
2021-01-02
 
3
2020-12-19
 
3
2021-01-04
 
2
2020-12-22
 
2
Other values (5)

Length

Max length10
Median length3
Mean length5.382978723
Min length3

Characters and Unicode

Total characters253
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)8.5%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan31
66.0%
2021-01-023
 
6.4%
2020-12-193
 
6.4%
2021-01-042
 
4.3%
2020-12-222
 
4.3%
2020-12-262
 
4.3%
2020-12-241
 
2.1%
2021-01-091
 
2.1%
2021-03-011
 
2.1%
2021-01-231
 
2.1%

Length

2022-05-09T21:17:24.750090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:24.859994image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan31
66.0%
2021-01-023
 
6.4%
2020-12-193
 
6.4%
2021-01-042
 
4.3%
2020-12-222
 
4.3%
2020-12-262
 
4.3%
2020-12-241
 
2.1%
2021-01-091
 
2.1%
2021-03-011
 
2.1%
2021-01-231
 
2.1%

Most occurring characters

ValueCountFrequency (%)
n62
24.5%
251
20.2%
039
15.4%
-32
12.6%
a31
12.3%
127
10.7%
94
 
1.6%
43
 
1.2%
62
 
0.8%
32
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number128
50.6%
Lowercase Letter93
36.8%
Dash Punctuation32
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
251
39.8%
039
30.5%
127
21.1%
94
 
3.1%
43
 
2.3%
62
 
1.6%
32
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
n62
66.7%
a31
33.3%
Dash Punctuation
ValueCountFrequency (%)
-32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common160
63.2%
Latin93
36.8%

Most frequent character per script

Common
ValueCountFrequency (%)
251
31.9%
039
24.4%
-32
20.0%
127
16.9%
94
 
2.5%
43
 
1.9%
62
 
1.2%
32
 
1.2%
Latin
ValueCountFrequency (%)
n62
66.7%
a31
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n62
24.5%
251
20.2%
039
15.4%
-32
12.6%
a31
12.3%
127
10.7%
94
 
1.6%
43
 
1.2%
62
 
0.8%
32
 
0.8%

_embedded_show_officialSite
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct38
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
https://www.netflix.com/title/81329144
 
2
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef
 
2
https://okko.tv/serial/prostokvashino
 
2
https://www.iqiyi.com/a_19rrhllpip.html
 
2
Other values (33)
35 

Length

Max length105
Median length70
Mean length45.74468085
Min length3

Characters and Unicode

Total characters2150
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)66.0%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://okko.tv/serial/prostokvashino
3rd rowhttps://okko.tv/serial/prostokvashino
4th rowhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html
5th rowhttps://www.ddtpro.com/

Common Values

ValueCountFrequency (%)
nan4
 
8.5%
https://www.netflix.com/title/813291442
 
4.3%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
4.3%
https://okko.tv/serial/prostokvashino2
 
4.3%
https://www.iqiyi.com/a_19rrhllpip.html2
 
4.3%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
4.3%
https://www.iqiyi.com/lib/m_213579814.html2
 
4.3%
https://railromanesque.jp1
 
2.1%
https://www.ufc.tv/page/fightpass1
 
2.1%
http://www.wwe.com/shows/wwe-talking-smack1
 
2.1%
Other values (28)28
59.6%

Length

2022-05-09T21:17:24.969757image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan4
 
8.5%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
4.3%
https://okko.tv/serial/prostokvashino2
 
4.3%
https://www.iqiyi.com/a_19rrhllpip.html2
 
4.3%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
4.3%
https://www.iqiyi.com/lib/m_213579814.html2
 
4.3%
https://www.netflix.com/title/813291442
 
4.3%
https://play.tv2.no/programmer/serier/hjerteslag1
 
2.1%
https://www.youtube.com/c/worldwartwo/playlists?view=50&sort=dd&shelf_id=51
 
2.1%
https://www.youtube.com/watch?v=ksjjpb-ekde&list=plv8q_exbqpnah3pkcng8ao4sbwxqfdjsy1
 
2.1%
Other values (28)28
59.6%

Most occurring characters

ValueCountFrequency (%)
t173
 
8.0%
/168
 
7.8%
s113
 
5.3%
w102
 
4.7%
.96
 
4.5%
e94
 
4.4%
o94
 
4.4%
h86
 
4.0%
i84
 
3.9%
p80
 
3.7%
Other values (61)1060
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1457
67.8%
Other Punctuation328
 
15.3%
Decimal Number184
 
8.6%
Uppercase Letter127
 
5.9%
Dash Punctuation21
 
1.0%
Math Symbol19
 
0.9%
Connector Punctuation14
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t173
 
11.9%
s113
 
7.8%
w102
 
7.0%
e94
 
6.5%
o94
 
6.5%
h86
 
5.9%
i84
 
5.8%
p80
 
5.5%
l67
 
4.6%
a62
 
4.3%
Other values (16)502
34.5%
Uppercase Letter
ValueCountFrequency (%)
P12
 
9.4%
M8
 
6.3%
T8
 
6.3%
L8
 
6.3%
A8
 
6.3%
Y7
 
5.5%
N7
 
5.5%
O6
 
4.7%
W6
 
4.7%
B6
 
4.7%
Other values (16)51
40.2%
Decimal Number
ValueCountFrequency (%)
432
17.4%
131
16.8%
324
13.0%
223
12.5%
517
9.2%
016
8.7%
612
 
6.5%
911
 
6.0%
810
 
5.4%
78
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/168
51.2%
.96
29.3%
:43
 
13.1%
?9
 
2.7%
&6
 
1.8%
%6
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
-21
100.0%
Math Symbol
ValueCountFrequency (%)
=19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1584
73.7%
Common566
 
26.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t173
 
10.9%
s113
 
7.1%
w102
 
6.4%
e94
 
5.9%
o94
 
5.9%
h86
 
5.4%
i84
 
5.3%
p80
 
5.1%
l67
 
4.2%
a62
 
3.9%
Other values (42)629
39.7%
Common
ValueCountFrequency (%)
/168
29.7%
.96
17.0%
:43
 
7.6%
432
 
5.7%
131
 
5.5%
324
 
4.2%
223
 
4.1%
-21
 
3.7%
=19
 
3.4%
517
 
3.0%
Other values (9)92
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t173
 
8.0%
/168
 
7.8%
s113
 
5.3%
w102
 
4.7%
.96
 
4.5%
e94
 
4.4%
o94
 
4.4%
h86
 
4.0%
i84
 
3.9%
p80
 
3.7%
Other values (61)1060
49.3%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct28
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.63829787
Minimum0
Maximum93
Zeros1
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:25.086100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q118
median39
Q354
95-th percentile82.5
Maximum93
Range93
Interquartile range (IQR)36

Descriptive statistics

Standard deviation25.99450237
Coefficient of variation (CV)0.7094899021
Kurtosis-0.7545766893
Mean36.63829787
Median Absolute Deviation (MAD)20
Skewness0.4214490837
Sum1722
Variance675.7141536
MonotonicityNot monotonic
2022-05-09T21:17:25.183439image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
544
 
8.5%
183
 
6.4%
393
 
6.4%
283
 
6.4%
13
 
6.4%
712
 
4.3%
62
 
4.3%
242
 
4.3%
462
 
4.3%
412
 
4.3%
Other values (18)21
44.7%
ValueCountFrequency (%)
01
 
2.1%
13
6.4%
31
 
2.1%
62
4.3%
71
 
2.1%
102
4.3%
131
 
2.1%
183
6.4%
192
4.3%
221
 
2.1%
ValueCountFrequency (%)
931
 
2.1%
891
 
2.1%
841
 
2.1%
791
 
2.1%
722
4.3%
712
4.3%
611
 
2.1%
571
 
2.1%
544
8.5%
521
 
2.1%

_embedded_show_dvdCountry
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
47 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters141
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan47
100.0%

Length

2022-05-09T21:17:25.277249image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:17:25.357524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan47
100.0%

Most occurring characters

ValueCountFrequency (%)
n94
66.7%
a47
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter141
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n94
66.7%
a47
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin141
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n94
66.7%
a47
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n94
66.7%
a47
33.3%

_embedded_show_summary
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct39
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size504.0 B
nan
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>
 
2
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>
 
2
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>
 
2
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
 
2
Other values (34)
35 

Length

Max length1129
Median length428
Mean length363.6382979
Min length3

Characters and Unicode

Total characters17091
Distinct characters99
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)70.2%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd rownan
3rd rownan
4th row<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>
5th rownan

Common Values

ValueCountFrequency (%)
nan4
 
8.5%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
4.3%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
4.3%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>2
 
4.3%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
4.3%
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>2
 
4.3%
<p>Comedian Yamasato Ryota enters a cafe to prepare a story. Trivial incidents unfold there with the staff, TV people, the manager, and a handsome office worker. Little things bother them, and Yamasato's annoyance reaches its limit. He pulls up his glasses, opens his notebook, and begins to write a story featuring a real-life actress in his notebook. For Yamasato, escaping reality is a "dream time" where he can forget the bad things. This is the start of Ryota Yamazato's fantasy story with the latest actresses and idols as the heroines! <br /> </p>1
 
2.1%
<p>The web series revolves around the life of university students.</p>1
 
2.1%
<p><b>I Like to Watch</b> is a 2019 American web series hosted by drag queens Trixie Mattel and Katya Zamolodchikova. The series was created by Fran Tirado, produced by Netflix, and streams on the network's YouTube channel. Produced in a similar format to Mattel and Zamolodchikova's web series <i>UNHhhh</i> and <i>The Trixie &amp; Katya Show</i>, <i>I Like to Watch</i> follows its hosts as they view and react to various Netflix Original Programming.</p>1
 
2.1%
<p>Destination UA is the project showing Ukraine from foreigner's perspective.</p><p>In First season we spent 30 days traveling along the tourist route called Golden Triangle – Kyiv-Lviv-Odesa.</p><p>We've visited more than 100 locations, tried over two dozen unique Ukrainian dishes, filmed ancient history places and modern spots. We had a lot of fun.</p><p>In the second season of the show we are visited next regions: Kyiv, Chernihiv, Sumy, Kharkiv, Poltava, Dnipro, Kherson, Mykolaiv, Vinnytsia, Zhytomyr.</p><p>Next 100 locations, interesting facts, adventures are waiting for you.</p>1
 
2.1%
Other values (29)29
61.7%

Length

2022-05-09T21:17:25.454134image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the169
 
6.0%
and107
 
3.8%
a81
 
2.9%
to70
 
2.5%
of68
 
2.4%
in49
 
1.7%
his32
 
1.1%
he30
 
1.1%
is25
 
0.9%
for23
 
0.8%
Other values (1144)2182
76.9%

Most occurring characters

ValueCountFrequency (%)
2778
16.3%
e1532
 
9.0%
t1108
 
6.5%
a1104
 
6.5%
i990
 
5.8%
o948
 
5.5%
n946
 
5.5%
s860
 
5.0%
r818
 
4.8%
h704
 
4.1%
Other values (89)5303
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter12794
74.9%
Space Separator2791
 
16.3%
Uppercase Letter599
 
3.5%
Other Punctuation494
 
2.9%
Math Symbol308
 
1.8%
Decimal Number43
 
0.3%
Dash Punctuation35
 
0.2%
Open Punctuation8
 
< 0.1%
Close Punctuation8
 
< 0.1%
Other Letter8
 
< 0.1%
Other values (3)3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1532
12.0%
t1108
 
8.7%
a1104
 
8.6%
i990
 
7.7%
o948
 
7.4%
n946
 
7.4%
s860
 
6.7%
r818
 
6.4%
h704
 
5.5%
d486
 
3.8%
Other values (24)3298
25.8%
Uppercase Letter
ValueCountFrequency (%)
T63
 
10.5%
S52
 
8.7%
L38
 
6.3%
F38
 
6.3%
A30
 
5.0%
W29
 
4.8%
C27
 
4.5%
M26
 
4.3%
U25
 
4.2%
H25
 
4.2%
Other values (17)246
41.1%
Other Punctuation
ValueCountFrequency (%)
,192
38.9%
.129
26.1%
/80
16.2%
'41
 
8.3%
"24
 
4.9%
!12
 
2.4%
:10
 
2.0%
?3
 
0.6%
;2
 
0.4%
&1
 
0.2%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Decimal Number
ValueCountFrequency (%)
016
37.2%
110
23.3%
97
16.3%
35
 
11.6%
24
 
9.3%
41
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-27
77.1%
7
 
20.0%
1
 
2.9%
Space Separator
ValueCountFrequency (%)
2778
99.5%
 13
 
0.5%
Math Symbol
ValueCountFrequency (%)
<154
50.0%
>154
50.0%
Open Punctuation
ValueCountFrequency (%)
(7
87.5%
[1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
)7
87.5%
]1
 
12.5%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13384
78.3%
Common3690
 
21.6%
Cyrillic9
 
0.1%
Katakana4
 
< 0.1%
Han4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1532
 
11.4%
t1108
 
8.3%
a1104
 
8.2%
i990
 
7.4%
o948
 
7.1%
n946
 
7.1%
s860
 
6.4%
r818
 
6.1%
h704
 
5.3%
d486
 
3.6%
Other values (44)3888
29.0%
Common
ValueCountFrequency (%)
2778
75.3%
,192
 
5.2%
<154
 
4.2%
>154
 
4.2%
.129
 
3.5%
/80
 
2.2%
'41
 
1.1%
-27
 
0.7%
"24
 
0.7%
016
 
0.4%
Other values (20)95
 
2.6%
Cyrillic
ValueCountFrequency (%)
о3
33.3%
Х1
 
11.1%
д1
 
11.1%
ч1
 
11.1%
у1
 
11.1%
м1
 
11.1%
й1
 
11.1%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17048
99.7%
None15
 
0.1%
Punctuation9
 
0.1%
Cyrillic9
 
0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2778
16.3%
e1532
 
9.0%
t1108
 
6.5%
a1104
 
6.5%
i990
 
5.8%
o948
 
5.6%
n946
 
5.5%
s860
 
5.0%
r818
 
4.8%
h704
 
4.1%
Other values (66)5260
30.9%
None
ValueCountFrequency (%)
 13
86.7%
ā1
 
6.7%
æ1
 
6.7%
Punctuation
ValueCountFrequency (%)
7
77.8%
1
 
11.1%
1
 
11.1%
Cyrillic
ValueCountFrequency (%)
о3
33.3%
Х1
 
11.1%
д1
 
11.1%
ч1
 
11.1%
у1
 
11.1%
м1
 
11.1%
й1
 
11.1%
Dingbats
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638024506
Minimum1608499007
Maximum1652117460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size504.0 B
2022-05-09T21:17:25.590753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1608499007
5-th percentile1609799896
Q11626079076
median1645408020
Q31650364384
95-th percentile1651949892
Maximum1652117460
Range43618453
Interquartile range (IQR)24285307.5

Descriptive statistics

Standard deviation15152330.35
Coefficient of variation (CV)0.009250368537
Kurtosis-0.661572022
Mean1638024506
Median Absolute Deviation (MAD)6354024
Skewness-0.9082452064
Sum7.698715177 × 1010
Variance2.295931151 × 1014
MonotonicityNot monotonic
2022-05-09T21:17:25.690544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
16098872012
 
4.3%
16482170292
 
4.3%
16513386482
 
4.3%
16097998962
 
4.3%
16184666822
 
4.3%
16491780842
 
4.3%
16238295291
 
2.1%
16457531591
 
2.1%
16521174601
 
2.1%
16465289861
 
2.1%
Other values (31)31
66.0%
ValueCountFrequency (%)
16084990071
2.1%
16093598271
2.1%
16097998962
4.3%
16098872012
4.3%
16114368421
2.1%
16184666822
4.3%
16238295291
2.1%
16238296751
2.1%
16246469541
2.1%
16275111981
2.1%
ValueCountFrequency (%)
16521174601
2.1%
16520806361
2.1%
16520294141
2.1%
16517643421
2.1%
16517620441
2.1%
16514965421
2.1%
16514170271
2.1%
16513386482
4.3%
16509491161
2.1%
16509088001
2.1%

_links_self_href
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size504.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2312227
 
1
https://api.tvmaze.com/episodes/2013871
 
1
https://api.tvmaze.com/episodes/2065447
 
1
https://api.tvmaze.com/episodes/2090654
 
1
Other values (42)
42 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters1833
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
2.1%
https://api.tvmaze.com/episodes/23122271
 
2.1%
https://api.tvmaze.com/episodes/20138711
 
2.1%
https://api.tvmaze.com/episodes/20654471
 
2.1%
https://api.tvmaze.com/episodes/20906541
 
2.1%
https://api.tvmaze.com/episodes/20906551
 
2.1%
https://api.tvmaze.com/episodes/21692031
 
2.1%
https://api.tvmaze.com/episodes/23122231
 
2.1%
https://api.tvmaze.com/episodes/23122241
 
2.1%
https://api.tvmaze.com/episodes/23122251
 
2.1%
Other values (37)37
78.7%

Length

2022-05-09T21:17:25.799725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
2.1%
https://api.tvmaze.com/episodes/23244321
 
2.1%
https://api.tvmaze.com/episodes/19640001
 
2.1%
https://api.tvmaze.com/episodes/19954051
 
2.1%
https://api.tvmaze.com/episodes/20077601
 
2.1%
https://api.tvmaze.com/episodes/19857891
 
2.1%
https://api.tvmaze.com/episodes/20396221
 
2.1%
https://api.tvmaze.com/episodes/20396231
 
2.1%
https://api.tvmaze.com/episodes/23244271
 
2.1%
https://api.tvmaze.com/episodes/23244281
 
2.1%
Other values (37)37
78.7%

Most occurring characters

ValueCountFrequency (%)
/188
 
10.3%
t141
 
7.7%
p141
 
7.7%
s141
 
7.7%
e141
 
7.7%
a94
 
5.1%
i94
 
5.1%
.94
 
5.1%
m94
 
5.1%
o94
 
5.1%
Other values (16)611
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1175
64.1%
Other Punctuation329
 
17.9%
Decimal Number329
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t141
12.0%
p141
12.0%
s141
12.0%
e141
12.0%
a94
8.0%
i94
8.0%
m94
8.0%
o94
8.0%
h47
 
4.0%
d47
 
4.0%
Other values (3)141
12.0%
Decimal Number
ValueCountFrequency (%)
271
21.6%
944
13.4%
139
11.9%
038
11.6%
328
 
8.5%
426
 
7.9%
823
 
7.0%
722
 
6.7%
619
 
5.8%
519
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/188
57.1%
.94
28.6%
:47
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1175
64.1%
Common658
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/188
28.6%
.94
14.3%
271
 
10.8%
:47
 
7.1%
944
 
6.7%
139
 
5.9%
038
 
5.8%
328
 
4.3%
426
 
4.0%
823
 
3.5%
Other values (3)60
 
9.1%
Latin
ValueCountFrequency (%)
t141
12.0%
p141
12.0%
s141
12.0%
e141
12.0%
a94
8.0%
i94
8.0%
m94
8.0%
o94
8.0%
h47
 
4.0%
d47
 
4.0%
Other values (3)141
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/188
 
10.3%
t141
 
7.7%
p141
 
7.7%
s141
 
7.7%
e141
 
7.7%
a94
 
5.1%
i94
 
5.1%
.94
 
5.1%
m94
 
5.1%
o94
 
5.1%
Other values (16)611
33.3%

Interactions

2022-05-09T21:17:18.539103image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:07.806101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:09.909017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.032256image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.235127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.330089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.186554image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.256767image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.475445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.745885image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:08.175841image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.134710image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.254362image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.423876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.622581image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.363529image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.444541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.685547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.846648image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:08.395914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.239878image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.351640image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.526315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.800454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.470863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.561927image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.784610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.940529image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:08.616382image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.337676image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.455554image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.620078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.969371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.586601image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.665884image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.879498image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:19.036628image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:08.802242image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.432961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.643217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.717011image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:14.264227image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.702088image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.893798image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.982843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:19.242858image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:09.183348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.621507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.833392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.879559image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:14.533289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.863775image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.072662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.188388image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:19.441202image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:09.331303image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.734815image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:11.945593image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.976580image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:14.677261image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.959373image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.183498image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.279422image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:19.548996image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:09.505022image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.844101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.044557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.105273image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:14.851492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.056013image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.288192image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.370231image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:19.647359image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:09.704198image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:10.938324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:12.138715image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:13.215380image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:15.014209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:16.157768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:17.382608image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:17:18.456458image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:17:25.882095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:17:26.004268image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:17:26.162990image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:17:26.325908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:17:26.667941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:17:19.825892image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:17:20.542254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:17:20.744482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:17:20.870698image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01988862https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24Chanyeol's Episode 244.024.0regular2020-12-1906:002020-12-18T21:00:00+00:0016.0None<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>41648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25nanhttps://www.vlive.tv/video/12163771.0nan<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1.608499e+09https://api.tvmaze.com/episodes/1977902
11989501https://www.tvmaze.com/episodes/1989501/troe-iz-prostokvasino-2x39-papa-ne-gorujПапа, не горюй2.039.0regular2020-12-19nan2020-12-19T00:00:00+00:0019.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg'}nan10892https://www.tvmaze.com/shows/10892/troe-iz-prostokvasinoТрое из ПростоквашиноAnimationRussian['Children', 'Family']Running7.015.01978-06-10nanhttps://okko.tv/serial/prostokvashino41.0nannan1.651339e+09https://api.tvmaze.com/episodes/2015818
21989503https://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirintСнежный лабиринт2.040.0regular2020-12-19nan2020-12-19T00:00:00+00:0019.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg'}nan10892https://www.tvmaze.com/shows/10892/troe-iz-prostokvasinoТрое из ПростоквашиноAnimationRussian['Children', 'Family']Running7.015.01978-06-10nanhttps://okko.tv/serial/prostokvashino41.0nannan1.651339e+09https://api.tvmaze.com/episodes/1964000
31988697https://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji第135集7.05.0regular2020-12-1910:002020-12-19T02:00:00+00:0020.0Nonenan35551https://www.tvmaze.com/shows/35551/soul-landSoul LandAnimationChinese['Action', 'Adventure', 'Anime', 'Fantasy']Running20.020.02018-01-13nanhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html89.0nan<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>1.643317e+09https://api.tvmaze.com/episodes/1995405
42138926https://www.tvmaze.com/episodes/2138926/tokyo-joshi-pro-wrestling-2020-12-19-tjpw-seno-merry-christmas-2020TJPW Se~No Merry Christmas! 20202020.044.0regular2020-12-1912:002020-12-19T03:00:00+00:00120.0Nonenan49740https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestlingTokyo Joshi Pro WrestlingSportsJapanese[]Running120.0120.02013-01-30nanhttps://www.ddtpro.com/13.0nannan1.651764e+09https://api.tvmaze.com/episodes/2007760
51962058https://www.tvmaze.com/episodes/1962058/heaven-officials-blessing-1x09-evil-taoist-scourgeEvil Taoist Scourge1.09.0regular2020-12-1911:002020-12-19T03:00:00+00:0025.0Nonenan51670https://www.tvmaze.com/shows/51670/heaven-officials-blessingHeaven Official's BlessingAnimationChinese['Drama', 'Anime', 'Fantasy', 'Romance']Running25.025.02020-10-31nanhttps://www.bilibili.com/tgcf52.0nan<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>1.637712e+09https://api.tvmaze.com/episodes/1985789
61972571https://www.tvmaze.com/episodes/1972571/the-wolf-1x29-episode-29Episode 291.029.0regular2020-12-19nan2020-12-19T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/2039622
71972572https://www.tvmaze.com/episodes/1972572/the-wolf-1x30-episode-30Episode 301.030.0regular2020-12-19nan2020-12-19T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/2039623
82071487https://www.tvmaze.com/episodes/2071487/youths-in-the-breeze-1x17-full-time-sworn-enemy-01FULL-TIME SWORN ENEMY #011.017.0regular2020-12-19nan2020-12-19T04:00:00+00:007.0Nonenan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/2324427
92071488https://www.tvmaze.com/episodes/2071488/youths-in-the-breeze-1x18-full-time-sworn-enemy-02FULL-TIME SWORN ENEMY #021.018.0regular2020-12-19nan2020-12-19T04:00:00+00:007.0Nonenan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
372311214https://www.tvmaze.com/episodes/2311214/ano-ko-no-yume-wo-mitan-desu-1x12-real"Real?"1.012.0regular2020-12-1900:152020-12-19T15:15:00+00:0029.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/404/1010042.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/404/1010042.jpg'}<p>Always alone at school, Yamasato was able to live away from reality by writing his fantasy stories in his notebook. In the story, he is the center of the world, and the heroine, by default, is Ai (Hashimoto Ai), the popular girl at the school. But one day when he opened his notebook, he found the rest of the story he had never written... </p>61536https://www.tvmaze.com/shows/61536/ano-ko-no-yume-wo-mitan-desuAno ko no Yume wo Mitan DesuScriptedJapanese['Drama', 'Romance', 'Mystery']Ended30.029.02020-10-032020-12-19https://www.tv-tokyo.co.jp/anoyume/intro/0.0nan<p>Comedian Yamasato Ryota enters a cafe to prepare a story. Trivial incidents unfold there with the staff, TV people, the manager, and a handsome office worker. Little things bother them, and Yamasato's annoyance reaches its limit. He pulls up his glasses, opens his notebook, and begins to write a story featuring a real-life actress in his notebook. For Yamasato, escaping reality is a "dream time" where he can forget the bad things. This is the start of Ryota Yamazato's fantasy story with the latest actresses and idols as the heroines! <br /> </p>1.649793e+09https://api.tvmaze.com/episodes/2087588
381984911https://www.tvmaze.com/episodes/1984911/rwby-8x07-warWar8.07.0regular2020-12-1911:002020-12-19T16:00:00+00:0015.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/727216.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/727216.jpg'}<p><b>"</b><i>It's all out war in Atlas. Our heroes face an impossible problem. Where do they go from here?</i><b>"</b></p>4091https://www.tvmaze.com/shows/4091/rwbyRWBYAnimationEnglish['Action', 'Adventure', 'Anime', 'Science-Fiction']Running15.013.02013-07-18nanhttps://roosterteeth.com/series/rwby84.0nan<p>The future-fantasy world of Remnant is filled with ravenous monsters, treacherous terrain, and more villains than you can shake a sniper-scythe at. Fortunately, Beacon Academy is training Huntsman and Huntresses to battle the evils of the world, and Ruby, Weiss, Blake, and Yang are ready for their first day of class.</p>1.645408e+09https://api.tvmaze.com/episodes/2006091
391961288https://www.tvmaze.com/episodes/1961288/wwe-talking-smack-2020-12-19-december-19-2020December 19, 20202020.018.0regular2020-12-19nan2020-12-19T17:00:00+00:0030.0Nonenan19667https://www.tvmaze.com/shows/19667/wwe-talking-smackWWE Talking SmackTalk ShowEnglish['Sports']Running30.030.02016-08-02nanhttp://www.wwe.com/shows/wwe-talking-smack71.0nan<p>On <b>WWE Talking Smack</b>, Renee Young catches up with your favorite SmackDown Superstars after "Smackdown Live" airs on the USA Network to hear their thoughts on all of that evening's action.</p>1.648133e+09https://api.tvmaze.com/episodes/1995507
402042789https://www.tvmaze.com/episodes/2042789/ufc-fight-pass-prelims-2020-12-19-ufc-fight-night-198-thompson-vs-neal-prelimsUFC Fight Night 198: Thompson vs. Neal Prelims2020.054.0regular2020-12-19nan2020-12-19T17:00:00+00:0060.0Nonenan25294https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelimsUFC Fight Pass PrelimsSportsEnglish[]Running60.074.02017-01-15nanhttps://www.ufc.tv/page/fightpass39.0nan<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>1.646529e+09https://api.tvmaze.com/episodes/2008312
411988690https://www.tvmaze.com/episodes/1988690/um-actually-4x10-magic-the-gatheringMagic: the Gathering4.010.0regular2020-12-19nan2020-12-19T17:00:00+00:0030.0Nonenan50839https://www.tvmaze.com/shows/50839/um-actuallyUm, Actually...Game ShowEnglish[]Running30.030.02018-09-28nannan72.0nan<p>Introducing a game show of fandom minutiae one-upmanship, where nerds do what nerds do best: flaunt encyclopedic nerd knowledge at Millennium Falcon nerd-speed.</p>1.652117e+09https://api.tvmaze.com/episodes/2015837
421943281https://www.tvmaze.com/episodes/1943281/rail-romanesque-1x12-departure-onwardsDeparture! Onwards!1.012.0regular2020-12-19nan2020-12-19T17:00:00+00:005.0Nonenan50939https://www.tvmaze.com/shows/50939/rail-romanesqueRail RomanesqueAnimationJapanese['Comedy', 'Anime', 'Science-Fiction']Ended5.05.02020-10-032020-12-19https://railromanesque.jp24.0nan<p>Set in Hinomoto, a fictional version of Japan, where for a long time railway travel served as the most important form of transport. Each locomotive was paired with a humanoid control module, so-called Raillord, that aided the train operator. However, many rail lines had been discontinued due to the rising popularity of "aerocrafts," a safe and convenient aerial mode of transport. As such, their accompanying railroads also went into a deep sleep. Soutetsu had lost his entire family in a rail accident and was adopted into the Migita household, which runs a shochu brewery in the city of Ohitoyo. He returned to his hometown to save it from the potential water pollution that would occur if they accepted the proposal to build an aerocraft factory nearby. He woke up the Raillord Hachiroku by accident and became her owner. For different purposes, they agreed to help find her lost locomotive, with the help of his stepsister Hibiki, the town's mayor and local railway chief, Paulette and others.</p>1.645753e+09https://api.tvmaze.com/episodes/1996819
432037520https://www.tvmaze.com/episodes/2037520/lovely-bites-by-chef-lovely-1x06-dinner-made-with-loveDinner Made with Love1.06.0regular2020-12-19nan2020-12-19T17:00:00+00:0025.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/329/823876.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/329/823876.jpg'}<p>Chef Lovely creates an elegant dinner for close friends. She makes her Roasted Chicken with Pomegranate Glaze, Green Beans Over Lemon Ricotta and Sweet Potato and Gruyere Gratin. Plus, there's an Upside-Down Pear Tart for dessert. You can taste the love!</p>53754https://www.tvmaze.com/shows/53754/lovely-bites-by-chef-lovelyLovely Bites by Chef LovelyRealityEnglish[]Running25.025.02020-11-14nanhttps://www.oprah.com/app/lovely-bites.html19.0nan<p>Chef Connie "Lovely" Jackson brings the fun with recipes that are perfect for entertaining and celebrating festive occasions. <b>Lovely Bites</b> is produced for OWN by FishBowl Worldwide Media.</p>1.623830e+09https://api.tvmaze.com/episodes/2037724
441983274https://www.tvmaze.com/episodes/1983274/eides-spraksjov-6x05-gudbrandsdalen-avdeling-tromsGudbrandsdalen, avdeling Troms6.05.0regular2020-12-1921:502020-12-19T20:50:00+00:0050.0Nonenan51631https://www.tvmaze.com/shows/51631/eides-spraksjovEides språksjovTalk ShowNorwegian['Comedy']RunningNaN43.02017-01-11nanhttps://tv.nrk.no/serie/eides-spraaksjov3.0nan<p>Entertainment from here to the moon when Linda Eide and guests pay tribute and joke with language.</p>1.650017e+09https://api.tvmaze.com/episodes/2037725
451984914https://www.tvmaze.com/episodes/1984914/onyx-equinox-1x05-predationPredation1.05.0regular2020-12-1916:002020-12-19T21:00:00+00:0024.0None<p>As the group heads for Danibaan, one of them suffers a horrifying injury. With nowhere left to turn, they seek help from a mysterious healer.</p>48922https://www.tvmaze.com/shows/48922/onyx-equinoxOnyx EquinoxAnimationEnglish['Action', 'Adventure', 'Fantasy']Ended24.024.02020-11-212020-12-26https://www.crunchyroll.com/onyx-equinox46.0nan<p>A young Aztec boy is saved from death by the gods and chosen to act as ‘humanity's champion,' forced to discard his apathy toward his fellow man and prove humanity's potential in a fight that spans across fantastical-yet-authentic Mesoamerican cultures.</p>1.609360e+09https://api.tvmaze.com/episodes/1988424
461984187https://www.tvmaze.com/episodes/1984187/ufc-fight-night-2020-12-19-ufc-fight-night-183-thompson-vs-nealUFC Fight Night 183: Thompson vs. Neal2020.030.0regular2020-12-1922:002020-12-20T03:00:00+00:00335.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721046.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721046.jpg'}nan1596https://www.tvmaze.com/shows/1596/ufc-fight-nightUFC Fight NightSportsEnglish[]Running120.0190.02005-08-06nanhttp://www.ufc.com/93.0nan<p><b>UFC Fight Night</b> is a part of the Ultimate Fighting Championship (UFC) which is the largest mixed martial arts promotion company in the world featuring most of the top-ranked fighters in the sport. Based in the United States, the UFC produces events worldwide. The organization showcases nine weight divisions and abides by the Unified Rules of Mixed Martial Arts. The UFC has held over 300 events to date. Dana White serves as the president of the UFC while brothers Frank and Lorenzo Fertitta control the UFC's parent company, Zuffa, LLC. The first UFC event was held on November 12, 1993 at the McNichols Sports Arena in Denver, Colorado. The purpose of the early UFC competitions was to identify the most effective martial art in a real fight between competitors of different fighting disciplines, including boxing, Brazilian jiu-jitsu, Sambo, wrestling, Muay Thai, karate, judo, and other styles. In subsequent competitions, fighters began adopting effective techniques from more than one discipline, which indirectly helped create an entirely separate style of fighting known as present-day mixed martial arts.</p>1.651762e+09https://api.tvmaze.com/episodes/1993940